Tetrabenzoporphyrins as organic semiconductors for high-performance organic field-effect transistors: a structure-property perspective
Bibliographic record
Abstract
Organic electronic materials are crucial for next-generation flexible and lightweight devices. This review critically examines tetrabenzoporphyrins (BPs) as highly promising organic semiconductors for organic field-effect transistors (OFETs), with a particular focus on the impact of peripheral substituents on charge transport properties. We detail the synthetic methodologies for pristine and substituted BPs, including thermal precursor conversion, oxidative aromatization, and Heck reactions, enabling the precise introduction of meso- and benzo-substituents. Strategic derivatization with groups such as trimethylsilylethynyl, triisopropylsilylethynyl, alkyl, and aryl is shown to modulate intermolecular CH–π and π–π interactions, leading to diverse packing motifs such as one-dimensional slip-stacked, brickwork, herringbone, and layered structures. These varied molecular arrangements are demonstrated to critically influence carrier mobility and device performance. The review also discusses recent advances in tetrabenzodiazaporphyrins and supramolecular assemblies, highlighting their roles in enhancing thermal stability and charge transport. Experimental results, particularly single-crystal X-ray diffraction analyses and OFET characterizations, corroborate the significance of molecular packing in optimizing device performance. By elucidating the effects of substituent size, shape, and placement on molecular aggregation, this work provides comprehensive insights into BP-based OFETs. Ultimately, understanding these structure–function correlations offers valuable guidelines for the rational design of high-mobility, thermally robust organic semiconductors, paving the way for innovative applications in flexible electronics and advanced device architectures. This critical analysis provides strategic directions for future research and development, advancing the field of organic electronics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".